GKR: Bridging the Gap between Symbolic/structural and Distributional Meaning Representations

Aikaterini-Lida Kalouli, Richard Crouch, Valeria de Paiva


Abstract
Three broad approaches have been attempted to combine distributional and structural/symbolic aspects to construct meaning representations: a) injecting linguistic features into distributional representations, b) injecting distributional features into symbolic representations or c) combining structural and distributional features in the final representation. This work focuses on an example of the third and less studied approach: it extends the Graphical Knowledge Representation (GKR) to include distributional features and proposes a division of semantic labour between the distributional and structural/symbolic features. We propose two extensions of GKR that clearly show this division and empirically test one of the proposals on an NLI dataset with hard compositional pairs.
Anthology ID:
W19-3305
Volume:
Proceedings of the First International Workshop on Designing Meaning Representations
Month:
August
Year:
2019
Address:
Florence, Italy
Venue:
DMR
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
44–55
Language:
URL:
https://aclanthology.org/W19-3305
DOI:
10.18653/v1/W19-3305
Bibkey:
Cite (ACL):
Aikaterini-Lida Kalouli, Richard Crouch, and Valeria de Paiva. 2019. GKR: Bridging the Gap between Symbolic/structural and Distributional Meaning Representations. In Proceedings of the First International Workshop on Designing Meaning Representations, pages 44–55, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
GKR: Bridging the Gap between Symbolic/structural and Distributional Meaning Representations (Kalouli et al., DMR 2019)
Copy Citation:
PDF:
https://aclanthology.org/W19-3305.pdf
Code
 kkalouli/GKR_semantic_parser
Data
SNLI